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Item type:Publication, Access status: with files , Lessons learnt in creating and operating the RECONECT nature-based solutions massive open online course(Cambridge University Press (CUP), 2026-01-26); ; Massive open online courses (MOOCs) have emerged as powerful educational tools for disseminating complex scientific knowledge. This study examines the RECONECT MOOC, an innovative online learning platform designed to educate stakeholders about nature-based solutions (NbS) for hydrometeorological risk reduction. Developed by a multidisciplinary team of international experts, the course drew on diverse professional and geographical perspectives, across a range of national and sectoral contexts. Its primary aim to bridge the knowledge gap in climate adaptation strategies across diverse professional sectors. The research investigated the effectiveness of interactive, multimedia-based learning approaches in communicating advanced NbS concepts. Using the Sharable Content Object Reference Model (SCORM) framework, the course integrated multiple learning methods, including reading, listening, inquiry-based learning, discussion forums and practical application exercises. The MOOC was divided into six modules and targeted local authorities, policymakers, academics, postgraduate students and other stakeholders interested in climate resilience. Findings revealed that 90% of participants gained additional NbS knowledge, 69% reported a shift in perception and 62% felt confident applying what they learned. Participants valued the interactive resources and flexible, self-paced format. Overall, the study demonstrates that MOOCs can effectively support scientific knowledge dissemination and strengthen understanding of complex environmental solutions.Publicationtype: Journal Article19 7 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: with files , Combining machine learning and spatial data processing techniques for allocation of large-scale nature-based solutions(IWA Publishing, 2023-11-15); ; ; The escalating impacts of climate change trigger the necessity to deal with hydro-meteorological hazards. Nature-based solutions (NBSs) seem to be a suitable response, integrating the hydrology, geomorphology, hydraulic, and ecological dynamics. While there are some methods and tools for suitability mapping of small-scale NBSs, literature concerning the spatial allocation of large-scale NBSs is still lacking. The present work aims to develop new toolboxes and enhance an existing methodology by developing spatial analysis tools within a geographic information system (GIS) environment to allocate large-scale NBSs based on a multi-criteria algorithm. The methodologies combine machine learning spatial data processing techniques and hydrodynamic modelling for allocation of large-scale NBSs. The case studies concern selected areas in the Netherlands, Serbia, and Bolivia, focusing on three large-scale NBS: rainwater harvesting, wetland restoration, and natural riverbank stabilisation. Information available from the EC H2020 RECONECT project as well as other available data for the specific study areas was used. The research highlights the significance of incorporating machine learning, GIS, and remote sensing techniques for the suitable allocation of large-scale NBSs. The findings may offer new insights for decision-makers and other stakeholders involved in future sustainable environmental planning and climate change adaptation.Publicationtype: Journal Article14 194 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , A new flood risk assessment framework for evaluating the effectiveness of policies to improve urban flood resilience(2018-05-28); ; ; ; To better understand the impacts of flooding such that authorities can plan for adapting measures to cope with future scenarios, we have developed a modified Drivers-Pressures-State-Impact-Response (DPSIR) framework to allow policy makers to evaluate strategies for improving flood resilience in cities. We showed that this framework proved an effective approach to assessing and improving urban flood resilience, albeit with some limitations. This framework has difficulties in capturing all the important relationships in cities, especially with regards to feedbacks. There is therefore a need to develop improved techniques for understanding components and their relationships. While this research showed that risk assessment is possible even at the mega-city scale, new techniques will support advances in this field. Finally, a chain of models engenders uncertainties. However, the resilience approach promoted in this research, is an effective manner to work with uncertainty by providing the capacity to cope and respond to multiple scenarios.Publicationtype: Journal Article129 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , A framework for flood impact assessment in urban areas(IAHS Press, 2013); ; ; ; Urban flooding affects millions of people worldwide, and with urban populations projected to grow, this problem is likely to become more pressing in the future. Increasing urban flood resilience through the implementation of resilience strategies is a way to improve the management of flood risk. So that the effectiveness of various resilience strategies can be evaluated, it is vital that the impacts of flooding can be assessed in a comprehensive and consistent manner. To this end, a framework has been developed that will incorporate all the major impacts of floods. It has long been noted that the development of such a framework is fraught with difficulties, but it is necessary if we are to make progress in understanding the wider impacts of flooding. In this paper, the developing flood impact assessment framework is outlined, as well as laying out the principles that will underpin future research. © 2013 IAHS Press.Publicationtype: Conference Paper131